Generalized vector space model: Difference between revisions

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{{short description|Generalization of the vector space model used in information retrieval}}

{{Confusing|date=January 2010}}

The '''Generalized vector space model''' is a generalization of the [[vector space model]] used in [[information retrieval]]. Wong ''et al.''<ref name="wong">{{citation | chapter=Generalized vector spaces model in information retrieval | first1=S. K. M. | title=Proceedings of the 8th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '85 | pages=18–25 | last1=Wong | first2=Wojciech|last2=Ziarko|first3=Patrick C. N.|last3=Wong | publisher=[[Association for Computing Machinery|SIGIR ACM]] | date=1985-06-05| doi=10.1145/253495.253506 | isbn=0897911598 | doi-access=free }}</ref> presented an analysis of the problems that the pairwise orthogonality assumption of the [[vector space model]] (VSM) creates. From here they extended the VSM to the generalized vector space model (GVSM).

==Definitions==

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where ''s_i'' and ''s_j'' are senses of terms ''t_i'' and ''t_j'' respectively, maximizing <math>SCM \cdot SPE</math>.

Building also on the first approach, Waitelonis et. al.<ref>{{citation | title=Linked Data enabled Generalized Vector Space Model to improve document retrieval | url=http://ceur-ws.org/Vol-1581/paper4.pdf | last1= Waitelonis | first1=Jörg | first2=Claudia | last2=Exeler | last3=Sack| first3=Harald | publisher=ISWC 2015, CEUR-WS 1581 |date=2015-09-11}}</ref> have computed semantic relatedness from [[Linked data|Linked Open Data]] resources including [[DBpedia]] as well as the [[YAGO (database)|YAGO taxonomy]].

Thereby they exploits taxonomic relationships among semantic entities in documents and queries after [[Entity linking|named entity linking]].

== References ==